Neural network based analysis systems for detecting and analyzing vibration are known. One such system and method are disclosed in U.S. Pat. No. 6,301,572 B1 entitled “Neural Network Based Analysis Systems for Vibrational Analysis and Condition Monitoring” which was filed Oct. 9, 2001 and is assigned to the assignee hereof. The disclosure of the '572 patent is hereby incorporated herein by reference.
In the system and method of the '572 patent, time domain outputs from a vibration sensor coupled to an apparatus being monitored are transferred to the frequency domain. Frequency domain outputs can then be provided as inputs to a fuzzy adaptive resonance-type neural network. Outputs from the network can be coupled to an expert system for analysis, to display devices for presentation to an operator or for use for other control and information purposes.
While the system and method of the '572 patent are useful and effective for their intended purpose, that solution was directed primarily to addressing vibration signals. There is a need for and it would be desirable to be able to automatically detect anomalies in complex systems which are continually being monitored for any deviation from normal operating condition. It would be desirable if the monitoring system could automatically learn the characteristics of the anomalous condition and respond thereto by generating a control command or causing a selected indication to be produced.